International Journal of Computational Intelligence Systems

Network-on-chip (NoC) are considered the next generation of communication infrastructure, which will be omnipresent in most of industry, office and personal electronic systems. In platform-based methodology, an application is implemented by a set of collaborating intellectual properties (IPs) blocks....

Advanced engineering materials design involves the exploration of massive multidimensional feature spaces, the correlation of materials properties and the processing parameters derived from disparate sources. The search for alternative materials or processing property strategies, whether through analytical,...

In a multilingual country like India, a document may contain text words in more than one language. For a multilingual environment, multi lingual Optical Character Recognition (OCR) system is needed to read the multilingual documents. So, it is necessary to identify different language regions of the document...

This paper describes the first Artificial Bee Colony (ABC) Algorithm approach applied to nurse scheduling evaluated under different working environments. For this purpose, the model has been applied on a real hospital where data taken from different departments of the hospital were used and the schedules...

In the paper, we express uncertain assessments information in linguistic multi-criteria decision makings (LMCDMs) as linguistic intuitionistic fuzzy sets, i.e., the decision maker provides membership and non-membership fuzzy linguistic terms to represent uncertain assessments information of alternatives...

In this paper, several cross-entropy measures for linguistic hesitant intuitionistic fuzzy information have been developed which integrating cross-entropy measures of intuitionistic fuzzy sets and hesitant fuzzy linguistic sets. Some desirable properties of new cross-entropy measures have been studied....

Computer vision-based rice quality inspection has recently attracted increasing interest in both academic and industrial communities because it is a low-cost tool for fast, non-contact, nondestructive, accurate and objective process monitoring. However, current computer-vision system is far from effective...

The fuzzy regression control chart is a functional technique to evaluate the process in which the average has a trend and the data represents a linguistic or approximate value. In this study, the theoretical structure of the “α-level fuzzy midrange for α-cut fuzzy X -regression control chart” is proposed...

The Minkowski distance is a distance measure that generalizes a wide range of distances such as the Hamming and the Euclidean distance. In this paper, we develop a generalization of the Minkowski distance by using the induced ordered weighted averaging (IOWA) operator. We call it the induced Minkowski...

The convolutional neural networks (CNNs) are frequently used in the segmentation of histopathological whole slide image- (WSI) acquired breast lymph nodes. The first layers in deep network architectures generally encode the geometric and color properties of objects in the training set, while the last...

A new learning algorithm for advanced robot locomotion is presented in this paper. This method involves both Cellular Neural Networks (CNN) technology and an evolutionary process based on genetic algorithm (GA) for a learning process. Learning is formulated as an optimization problem. CNN Templates are...

This paper shows the implementation of a prototype of street theft detector using the deep learning technique R-CNN (Region-Based Convolutional Network), applied in the Command and Control Information System (C2IS) of National Police of Colombia, the prototype is implemented using three models of CNN...

A commercial territory design problem with compactness maximization criterion subject to territory balancing and connectivity is addressed. Four new heuristics based on Greedy Randomized Adaptive Search Procedures within a location-allocation scheme for this NP-hard combinatorial optimization problem...

This paper presents an accurate wearable fall detection system which can identify the occurrence of falls among elderly population. A waist worn tri-axial accelerometer was used to capture the movement signals of human body. A set of laboratory-based falls and activities of daily living (ADL) were performed...

Feature subset selection, applied as a pre- processing step to machine learning, is valuable in dimensionality reduction, eliminating irrelevant data and improving classifier performance. In the classic formulation of the feature selection problem, it is assumed that all the features are available at...

Protection of the environment is currently a high profile concern and this is resulting in more effective recycling and reuse of materials. This paper outlines a research project for developing and using a ‘Technology Hub’ framework combining Computational Intelligence – Rule-based...

This paper considers the problem of non-fragile finite-time guaranteed cost fuzzy control for continuous-time nonlinear systems. Firstly, the definition on finite-time stability (FTS) for continuous-time nonlinear systems is provided and we give a novel and explicit interpretation for non-fragile finite-time...

An incomplete uncertain preference relation (UPR) is typical in group decision making (GDM) for decision makers (DMs) to express preference over alternatives because of the information interaction barrier between people and decision making environment. Completing missing values can guarantee individual...

The estimation of cost and production functions in economics relies on standard specifications which are less than satisfactory in numerous situations. However, instead of fitting the data with a pre-specified model, Artificial Neural Networks (ANNs) let the data itself serve as evidence to support the...

Firefly algorithm (FA) is a prominent metaheuristc technique. It has been widely studied and hence there are a lot of modified FA variants proposed to solve hard optimization problems from various areas. In this paper an improved chaotic firefly algorithm (ICFA) is proposed for solving global optimization...

This paper studies the α-consensus value of a cooperative game with payoffs of triangular intuitionistic fuzzy numbers and gives the formation mechanism of the α-consensus value, as well as some properties. Using the extended Hukuhara difference of triangular intuitionistic fuzzy numbers, the α-consensus...

This paper addresses the Hybrid Flow Shop (HFS) scheduling problems to minimize the makespan value. In recent years, much attention is given to heuristic and search techniques. Genetic algorithms (GAs) are also known as efficient heuristic and search techniques. This paper proposes an efficient genetic...

In this paper, a deterministic global optimization algorithm is proposed for solving min-max and max-min linear fractional programming problem (P) which have broad applications in engineering, management science, nonlinear system, economics and so on. By utilizing equivalent problem (Q) of the (P) and...

In this paper, a direct formula is proposed for design of robust PID controller for sun tracker system using quadratic regulator approach with compensating pole (QRAWCP). The main advantage of the proposed approach is that, there is no need to use recently developed iterative soft computing techniques...

In this paper, we propose new methods to represent interdependence among alternative attributes and experts’ opinions by constructing Choquet integral using interval-valued intuitionistic fuzzy numbers. In the sequel, we apply these methods to solve the multiple attribute group decision-making (MAGDM)...

As a knowledge representation tool, ontologies have been widely applied in many fields such as knowledge management and information integration, etc. Ontology measurement is an important challenge in the field of knowledge management in order to manage the development of ontology based systems and reduce...

We present a new multidimensional model with textual dimensions based on a knowledge structure extracted from the texts, where any textual attribute in a database can be processed, and not only XML texts. This dimension allows to treat the textual data in the same way as the non-textual one in an automatic...

Rough set theory gives approximation models of complex knowledge structure. Agents are not present in the definition of the rough sets. Now we will show that a set of conflicting agents or active set can be used to model inconsistent decision in rough set theory. Agent models give us the logic structure...

In order to build human cognition features into the procedure of clustering, this paper introduces a novel text clustering system, CogTCA (Cognitive Text Clustering with Ants), which (1) represents texts according to four cognitive situation dimensions in form of cognitive situation matrices and vectors...

We study the dynamics of a network consisting of N diffusively coupled, stable-limit-cycle oscillators on which individual frequencies are parametrized by ωk , k = 1, . . . , N. We introduce a learning rule which influences the ωk by driving the system towards a consensual oscillatory state in which...

Classical DC-DC converters used in high voltage direct current (HVDC) power transmission systems, lack in terms of efficiency, reduced transfer gain and increased cost with sensor (voltage/current) numbers. Besides, the internal self-parasitic behavior of the power components reduces the output voltage...

Clustering by fast searching and finding density peaks (DPC) method can rapidly identify the centers of clusters which have relatively high densities and high distances according to a decision graph. Various methods have been introduced to extend the DPC model over the past five years. DPC was originally...

Data driven rank ordering refers to the rank ordering of new data items based on the ordering inherent in existing data items. This is a challenging problem, which has received increasing attention in recent years in the machine learning community. Its applications include product recommendation, information...

Purpose: To examine the impact of artificial intelligence-assisted social media marketing (AISMM)on the performance of start-up businesses of small and medium enterprises (SMEs) in Saudi Arabia. Design/methodology/approach: A survey technique was employed whereby primary and secondary data was collected,...

This short note is devoted to introduce the discussion carried out along this special issue on the concept of Soft Computing by key researchers in the field. We shall stress some aspects of the conception and origins of Soft Computing, supported by the scientific relevance of its participants. The contributors...

A novel algorithm of audio aggregation watermarking was proposed in this paper for copyright protection. The algorithm not only protects copyright of a single audio in audio aggregation but also protects copyright of the whole audio aggregation. The experimental results showed the watermark of aggregate...

This paper introduces a novel ensemble learning approach based on recurrent radial basis function networks (RRBFN) for time series prediction with the aim of increasing the prediction accuracy. Standing for the base learner in this ensemble, the adaptive recurrent network proposed is based on the nonlinear...

We often make decisions on the things we like, dislike, or even don’t care about. However, taking the right decisions becomes relatively difficult from a variety of items from different sources. Recommender systems are intelligent decision support software tools that help users to discover items that...

Multimedia conferencing is increasingly becoming a very important and popular application over Internet. Due to the complexity of asynchronous communications and handle large and dynamically concurrent processes for multimedia conferencing, which confront relevant challenge to achieve sufficient correctness...

Evaluation is a process that analyzes elements in order to achieve different objectives such as quality inspection, marketing and other fields in industrial companies. This paper focuses on sensory evaluation where the evaluated items are assessed by a panel of experts according to the knowledge acquired...

The term Soft Computing was coined by L.A. Zadeh in the early 90's. Since that time many researchers have tried to define it considering different approaches: main constituents, properties, abilities, etc. In addition, the term Computational Intelligence has also gained popularity having a somehow quite...

In Hliněná et al., Pre-orders and orders generated by uninorms, in 15th International Conference IPMU 2014, Proceedings, Part III, Montpellier, France, 2014, pp. 307–316 the authors, inspired by Karaçal and Kesicioğlu, A t-partial order obtained from t-norms, Kybernetika. 47 (2011), 300–314, introduced...

Global optimization for nonlinear function is a challenging issue. In this paper, an improved monarch butterfly algorithm based on local search and differential evolution is proposed. Local search strategy is first embedded into original monarch butterfly optimization to enhance the searching capability....

Based on the equivalence relation, we can partition a set U, formally, different equivalence relations correspond to different partitions of U. In this paper, based on Yager's work, we discuss how to compare the different partitions, moreover, we obtain some indexes to select a better partition from...

The calculation of the premium cost of an option exchange is usually computed by the different mathematical models that obtain the degree of uncertainty in the financial market by Black-Scholes method though such a degree is inaccurate. In order to improve the management of uncertainty the use of fuzzy...

Decision making is a common process in human activities. Every person or organization needs to make decisions besides dealing with uncertainty and vagueness associated with human cognition. The theory of fuzzy logic provides a mathematical base to model the uncertainities. Hesitant fuzzy linguistic term...

Based on a multi-class support vector machine, an urban real estate early warning model is constructed for the Beijing real estate market. The initial indicator system is established based on the historical development of Beijing's real estate market and the selection of real estate early warning...

There has been a significant increase in the improvement of response to disasters in crisis management supply chain. Due to their sudden occurrence, these disasters require a consequent quick and efficient response that depends on the ability of logistics systems to generate plans under a variety of...

Most modern products/processes usually have several quality characteristics that must be optimized simultaneously; this is called a multi-response parameter design problem. To overcome shortcomings in the literature, including insufficient accuracy of second-order polynomials, subjective determination...

Recognition of characteristic patterns is proposed in this paper in order to diagnose the presence of electromechanical faults in induction electrical machines. Two common faults are considered; broken rotor bars and mixed eccentricities. The presence of these faults leads to the appearance of frequency...

This paper provides a literature review in clinical decision support systems (CDSSs) with a focus on the way knowledge bases are constructed, and how inference mechanisms and group decision making methods are used in CDSSs. Particular attention is paid to the uncertainty handling capability of the commonly...

This paper is focused on α-generalized semantic resolution automated reasoning method in linguistic truth-valued lattice-valued propositional logic. Concretely, α-generalized semantic resolution for lattice-valued propositional logic ()P(X) is equivalently transformed into that for lattice-valued...

This contribution serves historical and philosophical reflecting cognitions on the role of Soft Computing in the 21st century. Referring to Magdalena's article in this issue, this paper considers the aspects of mixtures of techniques, the opposite pair "Hard Computing" and "Soft Computing", and Computational...

Like some social animal groups, the evolution of plant populations in nature also contains swarm intelligence. Aiming at the problem of swarm Unmanned Aerial Vehicles (UAVs) target searching in complex and unknown environments, this paper explores search models suitable for swarm UAVs by investigating...

To provide users with more suitable and personalized service, personalization is widely used in various fields. Current e-Learning systems search for learning resources using information search technology, based on the keywords that selected or inputted by the user. Due to lack of semantic analysis for...

The aim of this paper is to investigate intuitionistic fuzzy multiple attribute decision making problems with preference information on alternatives, in which the information on attribute weights is completely unknown and the attribute values and preference information on alternatives take the form of...

Multi-attribute group emergency decision making (MAGEDM) has become a valuable research topic in the last few years due to its effectiveness and reliability in dealing with real-world emergency events (EEs). Dynamic evolution and uncertain information are remarkable features of EEs. The former means...

Reinforcement learning (RL) aims to resolve the sequential decision-making under uncertainty problem where an agent needs to interact with an unknown environment with the expectation of optimising the cumulative long-term reward. Many real-world problems could benefit from RL, e.g., industrial robotics,...

Acid gas removal (AGR) units are widely used to remove CO2 and H2S from sour gas streams in natural gas processing. When foaming occurs in an AGR system, the efficiency of the process extremely decreases. In this paper, a novel approach is suggested to regularly predict the gas dew point temperature...

Artificial Immune Systems (AIS), which is inspired by the nature immune system, has been applied for solving complex computational problems in classification, pattern rec- ognition, and optimization. In this paper, the theory of the natural immune system is first briefly introduced. Next, we compare...

The problem considered in this article is how to solve the image correspondence problem in cases where it is important to measure changes in the contour, position, and spatial orientation of bounded regions. This article introduces a computational intelligence approach to the solution of this problem...

In this paper, the problem of measuring the degree of subsethood in the interval-valued fuzzy setting is addressed. Taking into account the widths of the intervals, two types of interval subsethood measures are proposed. Additionally, their relation and main properties are studied. These developments...

Environmental and demographic pressures have led to the current importance of Water Demand Management (WDM), where the concepts of efficiency and sustainability now play a key role. Water must be conveyed to where it is needed, in the right quantity, at the required pressure, and at the right time using...

Most of the evaluation problems are comprehensive and with ever-increasingly more uncertainties. By quantifying the involved uncertainties, Basic Uncertain Information can both well handle and merge those uncertainties in the input information. This study proposed a two-level comprehensive evaluation...

The purpose of this study is to introduce a new regression model, based on the least squares method, when the available data of both explanatory variable(s) and response variable are interval-valued fuzzy (IVF) numbers. The proposed method is based on a new metric on the space of IVF numbers, which is...

This paper focuses on a linguistic-valued temporal logic based reasoning formalism for dynamically modelling and merging information under uncertainty in some real world systems where the state of a system evolves over time and the transition through states depends on uncertain conditions. We provide...

The construction of belief intervals is crucial for decision-making in multi-attribute group information integration. Based on multi-adjoint and evidence theory, an approach to multi-criteria group decision-making(MCGDM) in intuitionistic fuzzy information system is proposed. First, the upper and lower...

Due to the mismatch between the order of costumers and the production capacity resulting from demand uncertainty, product shortages or wastes of production capacity occur. In response, the subcontracting of production among the plants occurs to diminish the influence of this mismatch on expected profits....

With respect to intuitionistic fuzzy multiple attribute decision making problems with preference information on alternatives and incomplete weight information, a method based the minimum deviation is proposed. Firstly, some operational laws of intuitionistic fuzzy numbers, score function and accuracy...

Rule acquisition is one of the main purposes in the analysis of decision formal contexts. In general, the number of implications in a decision formal context is an exponential increase to the scale of the database. So, it is important to introduce effective inference rules between implications for eliminating...

Failure mode and effect analysis (FMEA) is a powerful risk assessment tool to eliminate the risk and improve the reliability. In this article, a novel risk priorization model based on extended TODIM (an acronym in Portuguese of interactive and multiple attribute decision-making) method under interval-valued...

The last fifty years has witnessed considerable activity in research that develops computational approaches inspired by nature. There are a number of umbrella terms used by researchers to classify their contributions. This can cause problems in disseminating and sharing results and potentially restricts...

In this paper, we shall firstly illustrate why we should introduce set-valued stochastic integrals, and then we shall discuss some properties of set-valued stochastic processes and the relation between a set-valued stochastic process and its selection set. After recalling the Aumann type definition of...

Bayesian networks have been widely used for classification problems. These models, structure of the network and/or its parameters (probability distributions), are usually built from a data set. Sometimes we do not have information about all the possible values of the class variable, e.g. data about a...

Ambiguities represent uncertainty but also a fundamental item of discussion for who is interested in the interpretation of languages and it is actually functional for communicative purposes both in human–human communication and in human–machine interaction. This paper faces the need to address ambiguity...

Underwater sensor deployment for military surveillance is a significant challenge due to the inherent difficulties posed by the underwater channel in terms of sensing and communications between sensors, as well as the exorbitant cost of the sensors. As a result, these sensors must be deployed as efficiently...

In the knowledge economy, a key source of sustainable competitive advantage relies on the way to create, share, and utilize knowledge. Knowledge Management (KM) tools assumed an important role in supporting KM activities. The objective of this paper is to aid decision makers to identify the most appropriate...

People working in the fields of robotics, animation, computer graphics and computer vision, and biomechanics, find it difficult to conduct human motion simulations, such as lifting, walking and running. This is because it is difficult to predict all of the motion strategies in a variety of situations....

In face verification applications, precision rate and identifying liveness are two key factors. Traditional methods usually recognize global faces and can not gain good enough results when the faces are captured from different ages, or there are some interference factors, such as facial shade, etc. Besides,...

In supervised learning, some real problems require the response attribute to represent ordinal values that should increase with some of the explaining attributes. They are called classification problems with monotonicity constraints. Hyperrectangles can be viewed as storing objects in ℝn which can be...

Adding an additional degree of non-membership, K. T. Atanassov introduced the concept of the intuitionistic fuzzy (IF) set (IF-set), which has rarely been applied to the game theory yet. The aim of this paper is to develop the concept and methodology of matrix games with IF-set goals in which goals of...

Interval set theory and soft set theory are mathematical tools for dealing with uncertainty information. As a combination of interval set and soft set, recently, we introduced the new notion of interval soft sets. In this paper we further research interval soft sets and its application. We investigate...

Energy indicators for sustainable development which were introduced by the International Atomic Energy Agency in 2005 were used in this study to determine a renewable energy perspective for Turkey. The decision making includes social, economic, and environmental factors which affect each other resulting...

Probability density estimation (PDF) is a task of primary importance in many contexts, including Bayesian learning and novelty detection. Despite the wide variety of methods at disposal to estimate PDF, only a few of them are widely used in practice by data analysts. Among the most used methods are the...

With the increasing availability of pen-based user interfaces, we often come upon multiple data sets of online handwritten scripts such as letters, words, etc., that are collected based on a viable interface. In this paper, we set forward a new method for online handwritten Arabic scripts recognition....

While it has been correctly noted that the expression “soft computing” is employed in a variety of senses and characterizations to designate a wide array of technologies, we argue that the original motivation for the introduction of soft-computing methods was the need to cope with the complexity of existing...

Greenhouses cannot be easily controlled because their climate parameters are interrelated. This study contributes to increasing the quality and yield of greenhouses by saving time, energy, light and water consumption via measuring and controlling the climate parameters that are effective in forming climate...

A single machine scheduling problem with periodic maintenance is studied in this paper. Due to many uncertainties in reality, the processing time is recognized as an uncertain variable. The aim is to minimize the makespan at a confidence level. An uncertain chance-constrained programming model is developed...

A type of Takagi-Sugeno (T-S) Proportional-Integral (PI) fuzzy controllers is studied. The T-S PI fuzzy controller is formed by a T-S Proportional-Derivative (PD) fuzzy controller connected with an integrator. In this particular structure, the T-S PD fuzzy controller is a weighted sum of some linear...

This study proposes a mathematical model of clustered multi-temperature joint distribution in fuzzy environment. In this model, a Z-shaped function is used to depict customer satisfaction. For the imprecise model, triangular fuzzy numbers are used to represent travel times. By redefining the movement...

In this paper, information energy metric (IEM) is obtained by similarity computing for high-dimensional samples in a reproducing kernel Hilbert space (RKHS). Firstly, similar/dissimilar subsets and their corresponding informative energy functions are defined. Secondly, IEM is proposed for similarity...

Normal support vector machine (SVM) algorithms are not suitable for classification of large data sets because of high training complexity. This paper introduces a novel two-stage SVM classification approach for large data sets. Fast clustering techniques are introduced to select the training data from...

This paper contains some naïve reflections on the currently large field of Soft Computing. After some general considerations, and of recalling some successful well known examples, it is posed the relationship between Soft Computing and Machine Intelligence. Finally, and with the aim of taking into account...

In this article a fuzzy multiobjective chance constrained programming model is used for modeling and solving land allocation problems efficiently with the help of fuzzy goal programming. Optimal production of seasonal crops and related expenditures are considered from the viewpoint of proper utilization...

In this paper, a novel hybrid approach composed of adaptive neuro-fuzzy inference system (ANFIS) and imperialist competitive algorithm is proposed. The imperialist competitive algorithm (ICA) is used in this methodology to determine the most suitable initial membership functions of the ANFIS. The proposed...

In this paper, we present a new algorithm for visually significant feature points detection for efficient image indexing and retrieval. We propose a hybrid feature point detector based on edge maps obtained via spatial and wavelet methods. Proposed method is compared with other existing interest point...

COVID-19 is an infectious disease caused by severe acute respiratory syndrome (SARS)-CoV-2 virus. So far, more than 20 million people have been infected. With the rapid spread of COVID-19 in the world, most countries are facing the shortage of medical resources. As the most extensive detection technology...

Text summarization is a process of distilling the most important content from text documents. While human beings have proven to be extremely capable summarizers, computer based automatic abstracting and summarizing has proven to be extremely challenging tasks. In this paper we report our experience with...

Complex phenomena are perceived from different perspectives, diversified conceptual points of view and at various levels of granularity. Symbolic and sub-symbolic processing becomes an inherently visible computing practice. Distributed nature of perception becomes reflected in topologies of multi-agent...